Unravelling the dynamics of cyber financial frauds: empirical evidence and insights

Purpose This study aims to quantify the scale/incidence of cyber-financial fraud and examine critical evolutionary patterns that shape its trajectory across Indian states. Design/methodology/approach This study uses regression analysis on state-level panel data (2003–2004 to 2022–2023) to examine how the financial magnitude across major fraud categories influences cyber-financial fraud incidence. A similar approach is applied to four structured sub-periods to analyse these relationships and identify significant temporal shifts in the predictors. The use of Panel-Corrected Standard Errors (PCSE) for the full period, and a methodological shift from Pooled Ordinary Least Squares-robust standard errors to PCSE in the sub-period analyses, ensures methodological rigour and robustness. Findings The results reveal a significant, positive and differentiated financial impact of all fraud categories on overall cyber-financial fraud incidence. The amount involved in credit card-related frauds exerts the strongest influence, followed by internet banking and ATM/debit card frauds. Sub-period analyses confirm temporal variations in both the relative influence and statistical significance of these categories, underscoring evolving patterns in the predictors of cyber-financial fraud incidence. Practical implications The findings may inform policymakers in enhancing institutional responses, directing state-level interventions and formulating targeted public awareness campaigns to mitigate both the incidence and financial impact of such frauds. Originality/value The study provides novel perspectives into key drivers and their evolving dynamics in shaping cyber-financial fraud incidence, using a systematic methodology through full-period and sub-period analyses.